• Journal of Hospice and Palliative Care
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• v.18 no.3
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• pp.179-187
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• 2015

For patients who are near the end of life, an inevitable step is discussion of a do-not-resuscitate (DNR) order, which involves patients, their family members and physicians. To discuss DNR orders, patients and family members should know the meaning of the order and cardiopulmonary resuscitation (CPR) which includes chest compression, defibrillation, medication to restart the heart, artificial ventilation, and tube insertion in the respiratory tract. And the following issues should be considered as well: patients' and their families' autonomy, futility of treatment, and the right for death with dignity. Terminal cancer patients should be informed of what futility of treatment is, such as a low survival rate of CPR, unacceptable quality of life after CPR, and an irremediable disease status. In Korea, two different law suits related to life supporting treatments had been filed, which in turn raised public interest in death with dignity. Since the 1980s, knowledge of and attitude toward DNR among physicians and the public have been improved. However, most patients are still alienated from the decision making process, and the decision is often made less than a week before death. Thus, the DNR discussion process should be improved. Early palliative care should be adopted more widely.

• Environmental and Resource Economics Review
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• v.30 no.3
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• pp.365-393
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• 2021

Using the Choice Experiment Method, this paper identified whether subsidy to the household around landfil in Seoul metropolitan area is being provided corresponding to the scale of the environmental damage. Since 2001, the subsidy program has been operating for nearly 20 years to compensate for various environmental damage (foul odor, noise, air pollution, water pollution, etc.) from landfill site in the metropolitan area, but it is not clear on what ground the subsidy is allocated. This paper estimated the marginal WTP by attribute (odor, noise, air pollution, and water pollution) based on mixed logit model and compared them with current subsidy level per household in each town. As a result of the comparison, it was found that the subsidy for each town was not allocated in proportion to the amount of the marginal WTP for each household in the corresponding town. In addition, this paper constructs a level-by-level scenario for environmental improvement attributes and compares economic benefits and current subsidy levels. As a result, the current subsidy level is insufficient compared to the level at which environmental damage is completely eliminated, but excessive subsidy is allocated compared to partial improvement levels.

• Resources Recycling
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• v.30 no.5
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• pp.38-48
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• 2021

In this study, we determine the optimal process conditions for selectively recovering Si from a solar cell surface by removal of impurities (Al, Zn, Ag, etc.). To selectively recover Si from solar cells, leaching is performed using HCl solution and an ultrasonic cleaner. After leaching, the solar cells are washed using distilled water and dried in an oven. Decompression filtration is performed on the HCl solution, and ICP-OES (Inductively Coupled Plasma Optical Emission spectroscopy) full scan analysis is performed on the filtered solution. Furthermore, XRD (X-ray powder diffraction), XRF (X-ray fluorescence), and ICP-OES are performed on the dried solar cells after crushing, and the purity and recovery rate of Si are obtained. In this experiment, the concentration of acid solution, reaction temperature, reaction time, and ultrasonic intensity are considered as variables. The results show that the optimal process conditions for the selective recovery of Si from the solar cells are as follows: the concentration of acid solution = 3 M HCl, reaction temperature = 60℃, reaction time = 120 min, and ultrasonic intensity = 150 W. Further, the Si purity and recovery rate are 99.85 and 99.24%, respectively.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.36 no.6
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• pp.507-514
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• 2018

TSI (TPI-Slope Index) which is the combination of TPI (Topographic Position Index) and slope was newly proposed for landslide and applied to a landslide susceptibility model. To do this, we first compared the TPIs with various scale factors and found that TPI350 was the best fit for the study area. TPI350 was combined with slope to create TSI. TSI was evaluated using logistic regression. The evaluation showed that TSI can be used as a landslide factor. Then a logistic regression model was developed to assess the landslide susceptibility by adding other topographic factors, geological factors, and forestial factors. For this, landslide-related factors that can be extracted from DEM (Digital Elevation Model), soil map, and forest type map were collected. We checked these factors and excluded those that were highly correlated with other factors or not significant. After these processes, 8 factors of TSI, elevation, slope length, slope aspect, effective soil depth, tree age, tree density, and tree type were selected to be entered into the regression analysis as independent variables. Three models through three variable selection methods of forward selection, backward elimination, and enter method were built and evaluated. Selected variables in the three models were slightly different, but in common, effective soil depth, tree density, and TSI was most significant.

• Journal of Internet Computing and Services
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• v.20 no.5
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• pp.27-36
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• 2019

In this study, experiments on the improvement of the emotion classification, analysis and accuracy of EEG data were proceeded, which applied DEAP (a Database for Emotion Analysis using Physiological signals) dataset. In the experiment, total 32 of EEG channel data measured from 32 of subjects were applied. In pre-processing step, 256Hz sampling tasks of the EEG data were conducted, each wave range of the frequency (Hz); Theta, Slow-alpha, Alpha, Beta and Gamma were then extracted by using Finite Impulse Response Filter. After the extracted data were classified through Time-frequency transform, the data were purified through Independent Component Analysis to delete artifacts. The purified data were converted into CSV file format in order to conduct experiments of Machine learning algorithm and Arousal-Valence plane was used in the criteria of the emotion classification. The emotions were categorized into three-sections; 'Positive', 'Negative' and 'Neutral' meaning the tranquil (neutral) emotional condition. Data of 'Neutral' condition were classified by using Cz(Central zero) channel configured as Reference channel. To enhance the accuracy ratio, the experiment was performed by applying the attributes selected by ASC(Attribute Selected Classifier). In "Arousal" sector, the accuracy of this study's experiments was higher at "32.48%" than Koelstra's results. And the result of ASC showed higher accuracy at "8.13%" compare to the Liu's results in "Valence". In the experiment of Random Forest Classifier adapting ASC to improve accuracy, the higher accuracy rate at "2.68%" was confirmed than Total mean as the criterion compare to the existing researches.

• KIPS Transactions on Software and Data Engineering
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• v.12 no.2
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• pp.59-76
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• 2023

Since the COVID-19 era, the rise in apartment prices has been unconventional. In this uncertain real estate market, price prediction research is very important. In this paper, a model is created to predict the actual transaction price of future apartments after building a vast data set of 870,000 from 2015 to 2020 through data collection and crawling on various real estate sites and collecting as many variables as possible. This study first solved the multicollinearity problem by removing and combining variables. After that, a total of five variable selection algorithms were used to extract meaningful independent variables, such as Forward Selection, Backward Elimination, Stepwise Selection, L1 Regulation, and Principal Component Analysis(PCA). In addition, a total of four machine learning and deep learning algorithms were used for deep neural network(DNN), XGBoost, CatBoost, and Linear Regression to learn the model after hyperparameter optimization and compare predictive power between models. In the additional experiment, the experiment was conducted while changing the number of nodes and layers of the DNN to find the most appropriate number of nodes and layers. In conclusion, as a model with the best performance, the actual transaction price of apartments in 2021 was predicted and compared with the actual data in 2021. Through this, I am confident that machine learning and deep learning will help investors make the right decisions when purchasing homes in various economic situations.

• Journal of the HCI Society of Korea
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• v.9 no.2
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• pp.33-40
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• 2014

Selecting appropriate features that products or services should provide for users has been a critical decision making problem for designers. However, the existing feature selection methods have prominent limitations when figuring out how they perceive the features. For example, selecting features based on the users' preference without analyzing users' mental models might lead to the 'feature creep' phenomenon. In this study, we suggest the 'False belief technique' that is able to detect users' mental model for the products/services that are formed after being provided with new features. This technique will be utilized as a way forward to help the designer to determine what features should be included in the new product development.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.13 no.11
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• pp.5610-5614
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• 2012

Performance of catalyst was studied with various operating conditions for selective catalytic reduction of $NO_x$ with $NH_3$. It is confirmed that catalysts containing Mn and Cu have a good efficiency in the usage of oxygen by the $H_2$-TPR analysis. In the case of catalyst #1, $NO_x$ conversion was decrease with the increase of reaction temperature. But in the case of catalyst #2, $NO_x$ conversion was increased and then remained constant with the increase of reaction temperature. This phenomenon is due to the difference of the $NH_3$ oxidation of both catalysts.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.44 no.6 s.360
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• pp.69-76
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• 2007

A new circuit design for Bus-Invert Coding is presented in this paper. The new scheme sends the coding information through the bus-lines instead of the invert-line which has been used conventionally for many types of Bus-Invert algorithms. By employing a newly developed bus-driver called Flip-Driver and a selection circuit, it not only removes the invert-line but suppresses the additional bus-transitions in sending coding information. It is verified by simulations that the efficiency of various Bus-Invert algorithms is increased about 40% to 100% by employing the new design.

• Clean Technology
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• v.7 no.3
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• pp.195-202
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• 2001

In this study the trace of chlorinated organic compound in aqueous solution was separated by pervaporation process using crosslinked PDMS (polydimethylsiloxane) membrane. The flux of trichloroethylene(TCE) increased linearly with feed composition but the flux of water was slightly increased. The partial flux of TCE was greater than that of tetrachloroethylene(PCE). The partial flux of TCE was not changed with operating temperature, but increased rapidly with feed flow rates. High crosslinking density causes the reduction of solubility and diffusivity for target component. The reduction of flux and selectivity for TCE is due to the chain immobilization and reduction of diffusivity with crosslinking density.